Computing devices have long provided the ability to track a location relative to the surface of the Earth through receiving wireless signals from multiple global positioning system (GPS) satellites and deriving a current location from the indications of timing within those signals. Using GPS coordinates, computing devices have been able to update existing maps of a location or to form maps of unknown or previously untraveled locations on the Earth's surface. As the computing device travels a path, a virtual map of the path of travel may be formed using GPS coordinates. Furthermore, the position of the computing device within the virtual map may be ascertained and represented based on GPS coordinates.
Thus, users of such computing devices that receive GPS signals are able to form a virtual map of a traveled path and visualize their current location on the virtual map. Unfortunately, the availability of such functions provided by computing devices typically ceases once the users of those devices go indoors and/or under a structure or other formation that blocks access to GPS signals. Depending on the thickness and/or material makeup of portions of such structures, access to GPS signals may become intermittent or distorted, or may be entirely cut off.
Simultaneous localization and mapping (SLAM) techniques have been used to form virtual maps of indoor spaces in the absence of GPS signals. SLAM techniques rely on recognizing locations that have been previously visited. Accordingly, accurate implementation of SLAM techniques often requires complex perceptual sensors, such as Lidar sensors or image detection equipment, in order to accurately detect locations that have been previously visited. Forming a virtual map of an indoor space using consumer computing equipment, such as, a smart phone or tablet computer, remains difficult.